DOE (Design of Experiments) - Advance

Learn and improve your career prospect and help your organization to improve efficiency.

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Course Overview:

DOE is a structured statistical approach to improve a product/process performance. In DOE with a small number of experimental runs & very large data, significant improvements to process can be made.

DOE aids in improving product performance, develops efficient processes, quickly solves manufacturing problems, and assists in breakthrough discoveries by applying powerful statistical methods. A must for Six Sigma, DOE helps you find product and process performance levels where all process requirements are met at minimal cost. For additional information on Process Technologies' approach to DOE.

DOE (DESIGN OF EXPERIMENTS) - Advance

How You Will Benefit:

  • Understand of Why design of experiments (DOE) are more efficient and effective than one-at-a-time
  • Understand of Operational Acceptance Testing(OAT) experimentation
  • How to use the major terms used in designed experiments mean
  • Types of designed experiments and when they are best used
  • How to use basic tests of significance
  • How to plan a designed experiment.

Course Methodology

  • Presentations
  • Games
  • Case Studies
  • Audio – Video
  • Desk Top Exercise
  • Learning by Doing
  • Role Modeling

Who Should Attend?

Engineers, Design, technical support personnel in Process Improvement, QMS, / Lean, Six Sigma, Quality, Production

Course Content

Module 1: Why DOE?

  • Limitations of OATs(one-at-a-time) experimentation
  • How designed experiments overcome the limitations of OATs and are more effective and efficient way to characterize and improve processes and products.

Module 2: DOE Terminology

  • An explanation of the key terms used in designed experiments.

Module 3: Types of Designed Experiments

  • Full Factorials
  • Fractional Factorials
  • Screening Experiments
  • Mixture Experiments

What’s Included?

  • Specialized manual and course materials
  • Instruction by an expert facilitator
  • Small interactive classes

Module:4 Tests of Significance

  • ANOVA (Analysis of Variance)
  • Alpha and Beta Risks
  • Degrees of Freedom
  • Hypothesis Tests
  • t-Tests
  • F-Tests

Module 5: Setting Up a Designed Experiment

  • Design & Communicate the Objective
  • Define the Process
  • Select a Response and Measurement System
  • Select Factors to be Studied
  • Select the Experimental Design
  • Set Factor Levels
  • Final Design Considerations

Module 6: Experiment and Test & DOE Challenge

  • DOE Simulation with Game
  • An assessment of the learner’s progress